Acknowledgement
Authors are thankful to the reviewers for their valuable suggestions, which led to improvement over the earlier version of the paper. Authors are also thankful to SERB, New Delhi, India for providing the financial assistance to carry out the present work. Authors sincerely acknowledged the free access to data by statistical abstracts of United States.
References
- Arnab R (2004). Optional randomized response techniques for complex survey designs, Biometrical Journal, 46, 114-124. https://doi.org/10.1002/bimj.200210006
- Arnab R (2011). Alternative estimators for randomized response techniques in multi-character surveys, Communications in Statistics-Theory and Methods, 40, 1839-1848. https://doi.org/10.1080/03610921003714188
- Arnab R, Singh S, and North D (2012). Use of two decks of cards in randomized response techniques for complex survey designs, Communications in Statistics-Theory and Methods, 41, 3198-3210. https://doi.org/10.1080/03610926.2012.682634
- Arnab R and Singh S (2013). Estimation of mean of sensitive characteristics for successive sampling, Communications in Statistics-Theory and Methods, 42, 2499-2524. https://doi.org/10.1080/03610926.2011.605233
- Christofides TC (2003). A generalized randomized response technique, Metrika, 57, 195-200. https://doi.org/10.1007/s001840200216
- Chaudhuri A and Dihidar K (2009). Estimating means of stigmatizing qualitative and quantitative variables from discretionary responses randomized or direct, Sankhya, 71, 123-136.
- Diana G and Perri PF (2010). New scrambled response models for estimating the mean of a sensitive quantitative character, Journal of Apllied Statistics, 37, 1875-1890. https://doi.org/10.1080/02664760903186031
- Diana G and Perri PF (2011). A class of estimators for quantitative sensitive data, Stat Papers, 52, 633-650. https://doi.org/10.1007/s00362-009-0273-1
- Deville JC and Sarndal CE (1992). Calibration estimators in survey sampling, Journal of the American Statistical Association, 87, 376-382. https://doi.org/10.1080/01621459.1992.10475217
- Eichhorn BH and Hayre LS (1983). Scrambled randomized response method for obtaining sensitive quantitative data, Journal of Statistical Planning and Inference, 7, 307-316. https://doi.org/10.1016/0378-3758(83)90002-2
- Gupta S, Gupta B, and Singh S (2002). Estimation of sensitivity level of personal interview survey question, Journal of Statistical Planning and Inference, 100, 239-247. https://doi.org/10.1016/S0378-3758(01)00137-9
- Gupta S, Mehta S, Shabbir J, and Dass BK (2013). Generalized scrambling quantitative optional randomized response models, Communication in Statistics-Theory and Methods, 42, 4034-4042. https://doi.org/10.1080/03610926.2011.638427
- Greenberg BG, Kubler RR, and Horvitz DG (1971). Application of RR technique in obtaining quantitative data, Journal of the American Statistical Association, 66, 243-250. https://doi.org/10.1080/01621459.1971.10482248
- Horvitz DG, Shah BV, and Simmons WR (1967). The unrelated question randomized response model, Journal of the American Statistical Association, 65-72.
- Himmelfarb S and Edgell SE (1980). Additive constants model: A randomized response technique for eliminating evasiveness to quantitative response questions, Psychological Bulletin, 87, 525-530. https://doi.org/10.1037/0033-2909.87.3.525
- Hussain Z and Al-Zahrani B (2016). Mean and sensitivity estimation of a sensitive variable through additive scrambling, Communications in Statistics-Theory and Methods, 45, 182-193. https://doi.org/10.1080/03610926.2013.827722
- Kim JM and Elam ME (2007). A stratified unrelated question randomized response model, Statistical Papers, 48, 215-233. https://doi.org/10.1007/s00362-006-0327-6
- Lundstrom, S and Sarndal CE (1999). Calibration as a standard method for treatment of non-response, Journal of Official Statistics, 15, 305-327.
- Mangat NS and Singh S (1994). An optional randomised response sampling technique, Journal of Indian Statistical Association, 32, 71-75.
- Naeem N and Shabbir J (2016). Use of scrambled responses on two occasions successive sampling under non-response, Hacettepe University Bulletin of Natural Sciences and Engineering Series B: Mathematics and Statistics, 46.
- Pal S (2008). Unbiasedly estimating the total of a stigmatizing variable from a complex survey on permitting options for direct or randomized responses, Statistical Papers, 49, 157-164. https://doi.org/10.1007/s00362-006-0001-z
- Pollock KH and Bek Y (1976). A comparison of three randomized response models for quantitative data, Journal of the American Statistical Association, 71, 884-886. https://doi.org/10.1080/01621459.1976.10480963
- Perri PF and Diana G (2013). Scrambled response models Based on auxiliary variables, Advances in Theoretical and Applied Statistics(pp281-291), Springer, Berlin.
- Priyanka K and Trisandhya P (2019a). A Composite Class of Estimators using Scrambled Response Mechanism for Sensitive Population mean in Successive Sampling, Communications in Statistics-Theory and Methods, 48, 1009-1032. https://doi.org/10.1080/03610926.2017.1422762
- Priyanka K and Trisandhya P (2019b). A Item sum techniques for quantitative sensitive estimation on successive occasions, Communications for Statistical Applications and Methods, 26, 175-189. https://doi.org/10.29220/CSAM.2019.26.2.175
- Priyanka K, Trisandhya P, and Mittal R (2018). Dealing sensitive characters on successive occasions through a general class of estimators using scrambled response techniques, Metron, 76, 203-230. https://doi.org/10.1007/s40300-017-0131-1
- Priyanka K, Trisandhya P, and Mittal R (2019). Scrambled response Techniques in Two Wave Rotation Sampling for Estimating Population Mean of Sensitive Characteristics with Case Study, Journal of Indian Society of Agricultural Statistics, 73, 41-52.
- Randles R (1982). On the asymptotic normality of statistics with estimated parameters, Annals of Statistics, 10, 462-474. https://doi.org/10.1214/aos/1176345787
- Saha A (2007). A simple randomized response technique in complex surveys, Metron, LXV, 59-66.
- Singh GN, Suman S, Khetan M, and Paul C (2017). Some estimation procedures of sensitive character using scrambled response techniques in successive sampling, Communications in Statistics-Theory and Methods.
- Singh GN, Khetan M, and Suman S (2018). Assessment of Scrambled Response on Second Call in Two-Occasion Successive Sampling under Non-Response, Journal of Indian Society of Agricultural Statistics, 72, 147-156.
- Sanaullah A, Saleem I, Gupta S, and Hanif M (2020). Mean estimation with generalized scrambling using two-phase sampling, Communications in Statistics-Simulation and Computations.
- Wu JW, Tian GL, and Tang ML (2008). Two new models for survey sampling with sensitive characteristics: Design and Analysis, Metrika, 67, 251-263. https://doi.org/10.1007/s00184-007-0131-x
- Warner SL (1965). Randomized response: a survey technique for eliminating evasive answer bias, Journal of the American Statistical Association, 60, 63-69. https://doi.org/10.1080/01621459.1965.10480775
- Yan Z, Wang J, and Lai J (2009). An efficiency and protection degree-based comparison among the quantitative randomized response strategies, Communications in Statistics-Theory and Methods, 38, 400-408. https://doi.org/10.1080/03610920802220785
- Yu B, Jin Z, Tian J, and Gao G (2015). Estimation of sensitive proportion by randomized response data in successive sampling, Computational and Mathematical Methods in Medicine, 2015, 1-6.